• Journal of the Korean Society of Propulsion Engineers
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• v.3 no.1
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• pp.24-33
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• 1999

For performance prediction and diagnostics of gas turbine engines, linear and non-linear gas path analysis are applied. In order to find optimal instrument parameters to detect the physical faults such as (outing, erosion and corrosion, non-linear gas path analysis is used. A typical industrial gas turbine engine, TB5000, is used to study the effect of physical faults on engine performance. Through comparison of RMS error between linear and non-linear gas path analysis, the optimal instrument parameters can be defined. As a result, it is found that the linear GPA has the level of error introduced by the assumption of the linear mode: can be of the same order of magnitude as the fault being soughtwhile the non-linear GPA can be solved the non-linear relationships between dependent and independent parameters using an iterative method such as the Newton-Raphson method with sufficient accuracy.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.3
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• pp.51-57
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• 2004

An intelligent performance diagnostic computer program of a gas turbine using the NN(Neural Network) was developed. Recently on-condition performance monitoring of major gas path components using the GPA(Gas Path Analysis) method has been performed in analyzing of engine faults. However because the types and severities of engine faults are various and complex, it is not easy that all fault conditions of the engine would be monitored only by the GPA approach Therefore in order to solve this problem, application of using the NNs for learning and diagnosis would be required. Among then, a BPN (Back Propagation Neural Network) with one hidden layer, which can use an updating learning rate, was proposed for diagnostics of PT6A-62 turboprop engine in this work.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2003.10a
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• pp.267-270
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• 2003

An intelligent performance diagnostic computer program of a gas turbine using the NN(Neural Network) was developed. Recently on-condition performance monitoring of major gas path components using the GPA(Gas Path Analysis) method has been performed in analyzing of engine faults. However because the types and severities of engine faults are various and complex, it is not easy that all fault conditions of the engine would be monitored only by the GPA approach. Therefore in order to solve this problem, application of using the NNs for learning and diagnosis would be required. Among then, a BPN (Back Propagation Neural Network) with one hidden layer, which can use an updating learning rate, was proposed for diagnostics of PT6A-62 turboprop engine in this work.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.4
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• pp.311-320
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• 2021

A study is performed for the real time fault diagnosis during operation and health estimation relating to performance deterioration in a turbojet engine used for an unmanned air vehicle. For this study the real time dynamic model is derived from the transient thermodynamic gas path analysis. For real fault conditions which are manipulated for the simulation, the detection techniques are applied such as Kalman filter and probabilistic decision-making approach based on statistical hypothesis test. Thereby the effectiveness is verified by showing good fault detection and isolation performances. For the health estimation with measurement parameters, it shows using an assumed performance degradation that the method by adaptive Kalman filter is feasible in practice for a condition based diagnosis and maintenance.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.218-221
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• 2006

High reliability and minimization of operating cost are important problems for both engine-manufacturer and user in operation of gas-turbine engine, for which various performance diagnostics including a fault identification have been a major issue nowadays. Performance estimation in the off-design conditions, however, encounters problems of large errors and of poor convergence because of much required data to be evaluated. In this study, a diagnostics code of engine performance has been developed by using GPA(Gas Path Analysis). Quantitative performance deterioration of the turbo-shaft engine for SUAV has been estimated with altitude variation and is compared with that obtained by GSP code.

• Journal of the Korean Society of Propulsion Engineers
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• v.10 no.3
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• pp.82-89
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• 2006

Recently operation and maintenance cost of gas turbine engines has been issued as a major parameter in terms of designing and manufacturing. Accordingly, the conception that the maintenance and repair of an engine has to be conducted in assembled condition has been spreaded out. However, it is possible only if the prediction of the engine performance is clearly identified. In this study, therefore, a diagnostic code of the engine performance has been developed by using GPA(Gas Path Analysis) and Fuzzy Logic which can analyze the engine performance and estimate the health parameters. The prediction of the quantitative performance deterioration of the established model of the turbo-shaft engine for SUAV has been achieved in a satisfied level compared to that obtained by GSP code.

• Economic and Environmental Geology
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• v.55 no.3
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• pp.261-271
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• 2022

Six gas samples were collected from coal and coaly shale from core AA-1, which was acquired from the Asem-Asem Basin, southeast Kalimantan, Indonesia. These coalbed gas samples were analyzed for the molecular composition, carbon isotope (δ¹³C_CH4, δ¹³C_C2, and δ¹³C_CO2), hydrogen isotope (δD_CH4), hydrocarbon index (C_HC), and carbon dioxide-methane index (CDMI) to document their origin and methanogenic pathways. Core AA-1 successively consists of lower clastic sedimentary rocks (Sedimentary Unit-1, SU-1) containing coal and coaly shale, and upper limestone (Sedimentary Unit-2, SU-2), unconformably underlain by serpentinized basement interpreted as part of the Cretaceous Meratus subduction complex (MSC). The coal and coaly shale (SU-1) were deposited in a marshes nearby a small-scale river. Compositions of coalbed gases show that methane ranges from 87.35 to 95.29% and ethane ranges from 3.65 to 9.97%. Carbon isotope of coalbed methane (δ¹³C_CH4) ranges from -60.3 to -58.8‰, while hydrogen isotope (δD_CH4) ranges from -252.9 to -252.1‰. Carbon isotope of coalbed ethane (δ¹³C_C2) ranges from -32.8 to -31.2‰, carbon isotope of coalbed carbon dioxide (δ¹³C_CO2) ranges from -8.6 to -6.2‰. The coalbed CO₂ is interpreted to be an abiogenic origin based on a combination of δ¹³C_CO2 and CDMI and could have been transported from underlying CO₂ bearing MSC through faults. The methanogenic pathways of coalbed gases are interpreted to have originated from primary methyl-type fermentation and mixed with CO₂ reduction, affecting thermogenic non-marine coal-type gases based on analyses of isotopic ratios and various indexes.

• Tunnel and Underground Space
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• v.18 no.3
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• pp.175-184
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• 2008

In this study, state-of-the-art of $CO_2$ geological sequestration as a method of greenhouse gas reduction was reviewed. Thermal-Hydraulic-Mechanically(THM) coupled simulation technology and its application to a stability analysis of geological formation due to $CO_2$ injection as well as a leakage path analysis were investigated and introduced.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.13 no.3
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• pp.145-151
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• 2003

Using computational fluid dynamics (CFD) method, we investigated three-dimensional fluid flow field and particle movement with respect to the injected gas flow rate variation in typical cyclone separator system. The results of numerical investigation were deduced by coupling the analysis of fluid flow field with Wavier-stokes equation and the tracking of the particle trajectory with Langrangian approach. It was shown that the increasing of injected gas flow rate resulted in the increasing of pressure loss in the separator. This change of inner pressure had an effect on an aspect of the fluid flow in the separator. Particle movement was determined by fluid flow in the separator and was fully depended on a diameter of particles under the fixed flow rate. Increasing of injected gas flow rate was led to an increasing of the trace of particle, so the particles moved to the lower part of the separator. For this reason, the minimum diameters of the particles were decreased and increased the separation rate under the fixed particle diameter. In conclusion, the changes of injected gas flow rate have an important factor to the fluctuation of the fluid flow field and particle trajectory in the separator.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.594-600
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• 2016

The present study numerically investigated the gas leakage characteristics in a simplified underground combined cycle power plant. The effect of obstacles near a crack location on the gas concentration in the confined space was analyzed by using the lower flammable limit (LFL) of methane gas. When the jet flow was close to the vertical walls, the longitudinal leakage distance increased by about 60% (when an obstacles was present) compared to the case without any obstacle, because these obstacles prevented transverse flows. In addition, when an air filter was installed near to the trajectory of the gas flow, the longitudinal leakage distance was similar to the distance between the crack and obstacle, whereas the transverse leakage distance increased up to 8 times compared to the case without any obstacle. As the jet flow impacts on the obstacle and changes its direction, the gas flows recirculate. Therefore, it is necessary to consider the effect of the structure and facility locations on the trajectory of the jet flow to propose an accident prevention system in confined spaces.